Abstract
A Fuzzy Approach for a Multiobjective Selective Maintenance Problem
Highlights
Reliability is the probability of an item to perform consistently a required function or mission without failure for a stated condition or interval of time
We find that the cost and time of replaceable items are known but the cost and time of repairing a component depends on the type of repairing needed because of several diverse situations like uncertain judgements, unpredictable conditions or human error, etc, due to which it is not always necessary that we get a precise data. Such type of imprecise data can be very well handled by fuzzy numbers, we may consider that the cost and time of repair are triangular fuzzy numbers i.e., the component is subject to say three types of repairing
The optimal compromise objective values obtained after solving the formulated multiobjective nonlinear programming problem (MONLPP) [10] and crisp problem using Fuzzy Programming Problem (FPP) approach are shown in table 2
Summary
Reliability is the probability of an item to perform consistently a required function or mission without failure for a stated condition or interval of time. There are many systems which accomplish a sequence of operation with finite breaks at regular intervals These breaks give an opportunity to repair or replace deteriorated components in the system so as to improve the system reliability that eventually improve the functioning of the whole mission. The study of the selective maintenance in system was originally performed by Rice et al (1998) They modeled a system of identical parallel series components and developed a decision making model to optimize. Cassady et al (2001b) improved the selective maintenance by removing the structural restriction on subsystem and developing a general framework with binary state components. Many systems involve uncertainties and imprecision in data where the estimation of precise values of probabilities is very difficult In such scenario fuzzy reliability is of much help. The problem is illustrated in a numerical example with assumed data
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